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Food insecurity in the United States of America: an examination of race/ethnicity and nativity

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Abstract

Food insecurity is a persistent problem in the United States and is disproportionately distributed across racial/ethnic groups, with some evidence that non-Latino blacks and Latinos experience higher rates than non-Latino whites. But no nationally-representative study examines how race/ethnicity affects food insecurity for immigrants in the United States. Using new assimilation theory and the 1999–2010 waves (N = 32,464) of the National Health and Nutrition Examination Survey (NHANES), this study investigated the relationship between food insecurity and both race/ethnicity and nativity status. Results, when socioeconomic status is held constant, provide evidence for a nonwhite/white divide in food insecurity for both immigrants and the native-born. That is, blacks and Latinos – regardless of nativity status – are significantly more food insecure than both foreign- and native-born whites. These results provide insight into a continuing pattern of racial/ethnic inequality in the United States.

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  1. Individuals (and households) identified by the USDA as low or very low food security both have difficulty in acquiring food and experience reduced diet quality. Those classified as very low food security also report multiple instances when their food intake was reduced and normal eating patterns disrupted (Coleman-Jensen et al. 2016:4–5)

  2. The panethnic Latino category cannot be disaggregated into ethnicities in the public-use NHANES data (NCHS 2013).

  3. We shorten the label for racial/ethnic groups by dropping “non-Latino” for the rest of the paper.

  4. The “other race” participants were combined into this single category by NHANES and cannot be disaggregated in the public-use data (National Center for Health Statistics (NCHS) 2013).

  5. We tested for and found evidence of violations of the proportional odds assumption in our ordered regression models. In supplementary analyses, we analyzed the NHANES measure of food insecurity with multinomial regression and created two dichotomous versions of the original four category food insecurity variable (full food security vs. the other categories; full/marginal food security vs. low/very low food security) that we analyzed with logistic regression. Results from these models provided evidence of the same pattern of results that we identified with the ordered logistic regression; therefore, we chose to continue with our original modeling strategy.

  6. Practically, we used SAS Proc Surveymeans for our descriptive and Proc Surveylogistic for our analytical analyses. To properly adjust the data, we used the cluster (sdmvpsu), strata (sdmvstra), and weight (wtint4yr, wtint2yr) options (the appropriate NHANES variables are in parentheses). We used the formula in Table E in Johnson et al. (2013) to combine weights across survey cycles.

  7. In supplemental analysis, we compared results generated both with and without multiple imputation and found similar results.

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Acknowledgements

For helpful comments on a previous draft, we thank Christine Porter and Anna Zajacova.

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  1. Department of Sociology, University of Wyoming, 308 Arts and Sciences, 1000 E. University Avenue, Laramie, WY, 82071, USA

    Ana McCormick Myers & Matthew A. Painter II

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Myers, A.M., Painter, M.A. Food insecurity in the United States of America: an examination of race/ethnicity and nativity. Food Sec. 9, 1419–1432 (2017). https://doi.org/10.1007/s12571-017-0733-8

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